Monday, August 4, 2014

Introducing the Shiny App DThiring

Well it has a been a long time since I have written anything on this blog.  I am long overdue.  I've been terribly busy learning new things and getting on with life.  One of the things I have learned is building R applications using Shiny developed by RStudio.   The folks at RStudio have also created a way to deploy Shiny apps using Shinyapps.io.  Follow the link to DThiring

http://larrydag.shinyapps.io/dthiring/

I'm a big fan of Data Tau which is a Data Science equivalent to Hacker News.  Like Hacker News, Data Tau has a Who's Hiring comment on the first of every month.  It is a good resource for those looking to see relevant jobs in the Data Science world.  Well someone created a hiring listings aggregator called http://hnhiring.me/.  I decided I wanted to see if I could build a similar application using R and Shiny.

I will be posting the source code for this app to github in the near future.

If you have any ideas on how to improve this application let me know in this comment section.

Saturday, March 15, 2014

OpenOpt 0.53


I'm glad to inform you about new OpenOpt Suite release 0.53:
    Stochastic programming addon now is available for free
    Some minor changes
Regards, Dmitrey.

Sunday, December 15, 2013

OpenOpt Suite release 0.52

I'm glad to inform you about new OpenOpt Suite release 0.52 (2013-Dec-15):
    Minor interalg speedup
    oofun expression
    MATLAB solvers fmincon and fsolve have been connected
    Several MATLAB ODE solvers have been connected
    New ODE solvers, parameters abstol and reltol
    New GLP solver: direct
    Some minor bugfixes and improvements
Regards, Dmitrey.

Sunday, September 15, 2013

New OpenOpt Suite release 0.51


New OpenOpt suite v 0.51 has been released:
  • Some improvements for  FuncDesigner  automatic differentiation and QP
  • FuncDesigner now can model sparse (MI)(QC)QP
  • Octave QP solver has been connected
  • MATLAB solvers linprog (LP), quadprog (QP), lsqlin (LLSP), bintprog (MILP)
  • New NLP solver: knitro
  • Some elements of 2nd order interval analysis, mostly for interalg
  • Some interalg improvements
  • interalg can directly handle (MI)LP and (possibly nonconvex) (MI)(QC)QP
  • New classes: knapsack problem (KSP), bin packing problem (BPP), dominating set problem (DSP)
  • FuncDesigner can model SOCP
  • SpaceFuncs  has been adjusted for recent versions of Python and NumPy
visit http://openopt.org for more details.

Saturday, June 15, 2013

new OpenOpt Suite release 0.50

Hi all,
I'm glad to inform you about new OpenOpt Suite release 0.50 (2013-June-15):

    * interalg (solver with specifiable accuracy) now works many times (sometimes orders) faster on (possibly multidimensional) integration problems (IP) and on some optimization problems
    * Add modeling dense (MI)(QC)QP in FuncDesigner (alpha-version, rendering may work slowly yet)
    * Bugfix for cplex wrapper
    * Some improvements for FuncDesigner interval analysis (and thus interalg)
    * Add FuncDesigner interval analysis for tan in range(-pi/2,pi/2)
    * Some other bugfixes and improvements
    * (Proprietary) FuncDesigner stochastic addon now is available as standalone pyc-file, became available for Python3 as well

Regards, Dmitrey.

Friday, March 15, 2013

OpenOpt Suite release 0.45

I'm glad to inform you about new OpenOpt Suite release 0.45 (2013-March-15):
  * Essential improvements for FuncDesigner interval analysis (thus affect interalg)
  * Temporary walkaround for a serious bug in FuncDesigner automatic differentiation kernel due to a bug in some versions of Python or NumPy, may affect optimization problems, including (MI)LP, (MI)NLP, TSP etc
  * Some other minor bugfixes and improvements

Saturday, February 16, 2013

Google Statistician uses R and other programming tools

A great interview on the Simply Statistics blog with Google's Nick Chamandy, Phd in Statistics.  Explains that he mainly uses R among other tools to perform his work at Google.  Also of note is the active data science community within Google that uses R as well as some other interesting tools.  Note that they use a lot of data at Google, understandably, and that R usually can not handle the size.  They do a lot of ad hoc reduction of the data with tools like map reduce, Go, and even an R API.  I would love to see how they use the R API to assimilate data.

An interesting insight from the interview is the amount of programming done by the Statisticians.  It seems the culture at Google is to foster autonomy and let the modelers develop their own data manipulation from the raw data.  This requires a broader skillset beyond the statistical analysis tools.

I've found in my work that having knowledge in many tools like R,  CPLEX, and GLPK allows me to be a more effective in my work.  Recently I've been learning a lot of SQL using the PostgreSQL platform.  The tools of SQL combined with statistical tools like R make for a very strong combination.  I'm very agile in my work and can do a varied number of decision analysis.